This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2013 International Conference on Information Networking (ICOIN)
Ecsy-Recsy: Considering Sybil attack with time dynamics and economics in recommender system
Bangkok Thailand
January 28-January 30
ISBN: 978-1-4673-5740-1
Giseop Noh, School of Computer Science and Engineering Seoul National University Seoul, Korea 151-744
Young-myoung Kang, School of Computer Science and Engineering Seoul National University Seoul, Korea 151-744
Chong-kwon Kim, School of Computer Science and Engineering Seoul National University Seoul, Korea 151-744
There is no doubt on the popularity of online social networks (OSNs) nowadays. With the exponential growth of the OSNs, various recommender systems (RSs) are widely deployed onto the OSNs. The RSs provide users with customized information to the RSs' users. Meanwhile, nefarious users attempt to compromise the RSs at the same time. There have been a lot of researches to block or detect such the nefarious users in the last decade. However, almost all studies aim to prevent such an anomaly under assumptions that the attackers have unlimited resources with static time condition. We consider the attackers' economics and time dynamics by introducing the concept of stickiness and persistence in the RSs. Furthermore, we suggest an anomaly detection scheme named Ecsy-Recsy (Economics-based sybil detection in Recommender system) leveraging the stickiness and persistence. We evaluate the stickiness and persistence from experiment with our dataset in which we crawled from a real world RS. Our experiment shows that the stickiness and persistence are the powerful measures to reveal the condition of RS in dynamically changing time domain. The Ecsy-Recsy shows the good detection performance under the various anomalies (naive, random, and average Sybil attack).
Citation:
Giseop Noh, Young-myoung Kang, Chong-kwon Kim, "Ecsy-Recsy: Considering Sybil attack with time dynamics and economics in recommender system," icoin, pp.566-571, 2013 International Conference on Information Networking (ICOIN), 2013
Usage of this product signifies your acceptance of the Terms of Use.